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Hands-On Data Science with Anaconda

You're reading from  Hands-On Data Science with Anaconda

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Pages 364 pages
Edition 1st Edition
Languages
Authors (2):
Yuxing Yan Yuxing Yan
Profile icon Yuxing Yan
James Yan James Yan
Profile icon James Yan
View More author details

Table of Contents (15) Chapters

Preface Ecosystem of Anaconda Anaconda Installation Data Basics Data Visualization Statistical Modeling in Anaconda Managing Packages Optimization in Anaconda Unsupervised Learning in Anaconda Supervised Learning in Anaconda Predictive Data Analytics – Modeling and Validation Anaconda Cloud Distributed Computing, Parallel Computing, and HPCC References Other Books You May Enjoy

Summary

In this chapter, we first discussed sources of open data, which included The Bureau of Labor Statistics, the Census Bureau, Professor French's data library, the Federal Reserve's data library, and the UCI Machine Learning Depository. After that, we showed you how to input data; how to deal with missing data; how to sort, slice, and dice the datasets; and how to merge different datasets. Data output was discussed in detail. For different languages, such as Python, R, and Julia, several relevant packages for data manipulation were introduced and discussed.

In Chapter 4, Data Visualization, we will discuss data visualization in R, Python, and Julia separately. To make our visual presentation more eye catching, we will show how you to generate simple graphs and bar charts, as well as how to add trend lines and legends. Other explanations will include how to save...

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